Modeling Spectral–Temporal Data From Point Source Events Reising, Monica Morris, Max Vardeman, Stephen Vardeman, Stephen Higbee, Shawn
dc.contributor.department Statistics
dc.contributor.department Industrial and Manufacturing Systems Engineering 2018-02-18T13:53:45.000 2020-07-02T06:58:11Z 2020-07-02T06:58:11Z 2011-01-01
dc.description.abstract <p>In recent years, a great deal of effort has been invested in developing sensors to detect, locate, and identify “energetic” electromagnetic events. When observed through one type of imaging spectrometer, these events produce a data record that contains complete spectral and temporal information over the event’s evolution. This article describes the development of a statistical model for the data produced by a particular spectral–temporal sensor. While the application is unique in some ways, this approach to model building may be useful in other related contexts. Several plots, estimated parameters, and some additional details for an equation are provided in the Appendix which is available as supplementary material online.</p>
dc.description.comments <p>This article is published as "Modeling spectral-temporal data from point source events." <em>Technometrics</em>, 2011. Vol. 53, No. 2, pp. 183-195, DOI:10.1198/TECH.2011.09014. With Monica Reising, Max Morris, and Shawn Higbee.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 1094
dc.identifier.contextkey 10303501
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/95
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 02:34:01 UTC 2022
dc.source.uri 10.1198/TECH.2011.09014
dc.subject.disciplines Statistics and Probability
dc.subject.keywords Event discrimination
dc.subject.keywords Infrared
dc.subject.keywords Product correlation
dc.subject.keywords Pseudo-imaging
dc.subject.keywords Spectral imager
dc.title Modeling Spectral–Temporal Data From Point Source Events
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
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